Unit DIGITAL SIGNAL PROCESSING
- Course
- Electronic engineering for the internet-of-things
- Study-unit Code
- 70A00096
- Curriculum
- In all curricula
- Teacher
- Giuseppe Baruffa
- Teachers
-
- Giuseppe Baruffa
- Hours
- 72 ore - Giuseppe Baruffa
- CFU
- 9
- Course Regulation
- Coorte 2021
- Offered
- 2021/22
- Learning activities
- Affine/integrativa
- Area
- Attività formative affini o integrative
- Academic discipline
- ING-INF/03
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- - Properties of discrete systems and sequences
- Discrete Fourier transform
- Z transform
- Digital filter design
- Spectral estimation with digital systems
- SDR systems for IoT and aerospace
- Image processing for IoT and aerospace - Reference texts
- - S. Orfanidis, “Introduction to Signal Processing”, Prentice Hall
- Alan V Oppenheim, Ronald W. Schafer, “Discrete-Time Signal Processing,” 3rd Edition, Pearson
- R. Gonzalez, R. Woods, “Digital Image processing”, Pearson Education
- Personal slides - Educational objectives
- - understanding and designing digital FIR and IIR filters
- understanding, simulating, and designing spectral estimation schemes based upon the use of DFT and FFT
- understanding, simulating, and designing sampling rate conversion systems with either a direct or polyphase technique
- understanding, designing, and using an SDR system
- understanding and designing an image processing system - Prerequisites
- - signals theory
- fundamentals of telecommunications
- theory of probability and measurement - Teaching methods
- Face to face lessons of theoretical arguments are held using a PC with digital projector; integrations are developed using the multimedia blackboard.
Students are encouraged to carry a personal laptop PC for the exercises that will be held in the classroom. - Other information
- Further information will be available in the UniStudium web-page dedicated to this course, which is accessible to all the students enrolled in this course.
- Learning verification modality
- Grading is determined by the results of two examinations.
The first examination, in written form with open answers, verifies the theoretical and practical knowledge of the arguments presented during the lessons.
The second examination is a colloquium on the arguments presented during the lessons, with questions and open answers.
The final grade is determined by averaging the grades achieved during the two examinations.
Please note that, depending on the needs related to the Covid, the examination could consist only of the colloquium. - Extended program
- Ideal Sampling, Practical A/D and D/A Conversion. Quantization, quantization noise.
Introduction to Digital Signal Processing. Discrete time signals, vs Analog Signals, vs Digital Signals.
Discrete-Time Systems, stability and causality of discrete-time systems (LTI) – Discrete Time Impulse Response
Discrete time convolution
Difference Equation for IIR systems
DTFT (Discrete Time Fourier Transform) – Frequency Spectrum of Discrete Signals. Frequency Sampling of DTFT – DFT and IDFT. Fast Fourier Transform FFT.
Circular Convolution, implementation of Circular Convolution with Linear Convolution and Circular Prefix
DFT/FFT for spectral analysis of stationary signals. Frequency resolution. Windowing of data. - DFT/FFT for spectral analysis of non-stationary signals. Spectrogram.
FIR Filter Design with Windows Methods – traditional windows – Kaiser Window.
FIR Filter Design with Frequency Sampling method
Z transform.
Main Properties. Region of Convergence (RoC), Causality and Stability. Frequency Spectrum – relation with DTFT.
Inverse Z transform
Equivalent descriptions of Discrete Time Systems, Transfer Function – Sinusoidal response, Stationary time Response, Transient Response.
IIR Filter Design with Pole-Zero placement: First Order Filters, Parametric Filters, Notch and Comb Filters.
Interpolation and oversampling. Interpolation Filter Design – Polyphase interpolators. DAC Equalization, Multistage Interpolation.
Decimation, Decimation Filter design.
L/M Sampling rate Converters. Noise shaping quantizers.
Software Defined Radio (SDR) systems operational paradigm. Equivalence between BB and RF signals. Main algorithms used for digital filtering, digital down conversion and digital frequency synthesis, sampling rate conversion.
Multidimensional signals: images and video. Bidimensional sampling. 2D transforms. 2D filters, linear and non-linear.
Wavelet transform theory and its use in digital image processing applications.